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» Matching Algorithms Are Fast in Sparse Random Graphs
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97
Voted
CVPR
2008
IEEE
15 years 11 months ago
FusionFlow: Discrete-continuous optimization for optical flow estimation
Accurate estimation of optical flow is a challenging task, which often requires addressing difficult energy optimization problems. To solve them, most top-performing methods rely ...
Victor S. Lempitsky, Stefan Roth, Carsten Rother
JSAC
2011
116views more  JSAC 2011»
14 years 4 months ago
Low Complexity Outage Optimal Distributed Channel Allocation for Vehicle-to-Vehicle Communications
—Due to the potential of enhancing traffic safety, protecting environment, and enabling new applications, vehicular communications, especially vehicle-to-vehicle (V2V) communica...
Bo Bai, Wei Chen, Khaled Ben Letaief, Zhigang Cao
138
Voted
STOC
1997
ACM
257views Algorithms» more  STOC 1997»
15 years 1 months ago
Practical Loss-Resilient Codes
We present randomized constructions of linear-time encodable and decodable codes that can transmit over lossy channels at rates extremely close to capacity. The encoding and decod...
Michael Luby, Michael Mitzenmacher, Mohammad Amin ...
80
Voted
CVPR
2012
IEEE
12 years 12 months ago
KNN matting
We are interested in a general alpha matting approach for the simultaneous extraction of multiple image layers; each layer may have disjoint segments for material matting not limi...
Qifeng Chen, Dingzeyu Li, Chi-Keung Tang
88
Voted
KDD
2006
ACM
164views Data Mining» more  KDD 2006»
15 years 10 months ago
Sampling from large graphs
Given a huge real graph, how can we derive a representative sample? There are many known algorithms to compute interesting measures (shortest paths, centrality, betweenness, etc.)...
Jure Leskovec, Christos Faloutsos